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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 16 Jan 2012 03:50:58 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jan/16/t1326704053x1mwljck1cnwzz3.htm/, Retrieved Sun, 28 Apr 2024 15:51:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=161199, Retrieved Sun, 28 Apr 2024 15:51:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact208

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2012-01-16 08:50:58] [62e5aaf804a30a3c745be39dc891a0c9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14,14
14,16
14,21
14,26
14,29
14,32
14,33
14,39
14,48
14,44
14,46
14,48
14,53
14,58
14,62
14,62
14,61
14,65
14,68
14,7
14,78
14,84
14,89
14,89
15,13
15,25
15,33
15,36
15,4
15,4
15,41
15,47
15,54
15,55
15,59
15,65
15,75
15,86
15,89
15,94
15,93
15,95
15,99
15,99
16,06
16,08
16,07
16,11
16,15
16,18
16,3
16,42
16,49
16,5
16,58
16,64
16,66
16,81
16,91
16,92
16,95
17,11
17,16
17,16
17,27
17,34
17,39
17,43
17,45
17,5
17,56
17,65
17,62
17,7
17,72
17,71
17,74
17,75
17,78
17,8
17,86
17,88
17,89
17,94

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161199&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161199&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161199&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
114.14NANA-0.00917245370370348NA
214.16NANA0.0348553240740739NA
314.21NANA0.0443692129629627NA
414.26NANA0.0286747685185181NA
514.29NANA0.019299768518518NA
614.32NANA-0.00354745370370415NA
714.3314.334924768518514.34625-0.011325231481482-0.0049247685185172
814.3914.359924768518514.38-0.02007523148148050.0300752314814829
914.4814.403883101851914.4145833333333-0.01070023148148080.0761168981481504
1014.4414.429299768518514.4466666666667-0.01736689814814880.0107002314814828
1114.4614.453049768518514.475-0.02195023148148120.00695023148148266
1214.4814.469021990740714.5020833333333-0.0330613425925920.0109780092592615
1314.5314.52124421296314.5304166666667-0.009172453703703480.00875578703703717
1414.5814.592771990740714.55791666666670.0348553240740739-0.01277199074074
1514.6214.627702546296314.58333333333330.0443692129629627-0.00770254629629719
1614.6214.641174768518514.61250.0286747685185181-0.0211747685185184
1714.6114.666383101851914.64708333333330.019299768518518-0.0563831018518517
1814.6514.678535879629614.6820833333333-0.00354745370370415-0.0285358796296276
1914.6814.712841435185214.7241666666667-0.011325231481482-0.0328414351851833
2014.714.757008101851914.7770833333333-0.0200752314814805-0.0570081018518511
2114.7814.823883101851914.8345833333333-0.0107002314814808-0.0438831018518524
2214.8414.877633101851914.895-0.0173668981481488-0.037633101851851
2314.8914.936799768518514.95875-0.0219502314814812-0.0467997685185182
2414.8914.989855324074115.0229166666667-0.033061342592592-0.0998553240740723
2515.1315.075410879629615.0845833333333-0.009172453703703480.0545891203703732
2615.2515.181938657407415.14708333333330.03485532407407390.0680613425925909
2715.3315.255202546296315.21083333333330.04436921296296270.0747974537037042
2815.3615.300758101851915.27208333333330.02867476851851810.059241898148148
2915.415.350133101851915.33083333333330.0192997685185180.0498668981481476
3015.415.38811921296315.3916666666667-0.003547453703704150.0118807870370379
3115.4115.437841435185215.4491666666667-0.011325231481482-0.0278414351851843
3215.4715.480341435185215.5004166666667-0.0200752314814805-0.0103414351851825
3315.5415.538466435185215.5491666666667-0.01070023148148080.00153356481481737
3415.5515.579299768518515.5966666666667-0.0173668981481488-0.0292997685185146
3515.5915.620966435185215.6429166666667-0.0219502314814812-0.0309664351851833
3615.6515.654855324074115.6879166666667-0.033061342592592-0.00485532407407163
3715.7515.725827546296315.735-0.009172453703703480.024172453703704
3815.8615.815688657407415.78083333333330.03485532407407390.044311342592593
3915.8915.868535879629615.82416666666670.04436921296296270.0214641203703732
4015.9415.896591435185215.86791666666670.02867476851851810.043408564814813
4115.9315.929299768518515.910.0192997685185180.000700231481481239
4215.9515.94561921296315.9491666666667-0.003547453703704150.00438078703703759
4315.9915.973674768518515.985-0.0113252314814820.016325231481483
4415.9915.994924768518516.015-0.0200752314814805-0.0049247685185172
4516.0616.034716435185216.0454166666667-0.01070023148148080.0252835648148135
4616.0816.065133101851816.0825-0.01736689814814880.0148668981481492
4716.0716.103883101851816.1258333333333-0.0219502314814812-0.0338831018518491
4816.1116.139021990740716.1720833333333-0.033061342592592-0.0290219907407412
4916.1516.210410879629616.2195833333333-0.00917245370370348-0.0604108796296288
5016.1816.306105324074116.271250.0348553240740739-0.126105324074071
5116.316.367702546296316.32333333333330.0443692129629627-0.0677025462962924
5216.4216.407424768518516.378750.02867476851851810.0125752314814882
5316.4916.463466435185216.44416666666670.0192997685185180.0265335648148159
5416.516.50936921296316.5129166666667-0.00354745370370415-0.00936921296296234
5516.5816.568674768518516.58-0.0113252314814820.0113252314814822
5616.6416.632008101851816.6520833333333-0.02007523148148050.00799189814815193
5716.6616.715966435185216.7266666666667-0.0107002314814808-0.0559664351851836
5816.8116.775966435185216.7933333333333-0.01736689814814880.0340335648148162
5916.9116.834716435185216.8566666666667-0.02195023148148120.0752835648148142
6016.9216.891105324074116.9241666666667-0.0330613425925920.0288946759259296
6116.9516.98374421296316.9929166666667-0.00917245370370348-0.0337442129629615
6217.1117.094438657407417.05958333333330.03485532407407390.0155613425925978
6317.1617.169785879629617.12541666666670.0443692129629627-0.00978587962962862
6417.1617.215758101851817.18708333333330.0286747685185181-0.0557581018518469
6517.2717.262216435185217.24291666666670.0192997685185180.00778356481481879
6617.3417.29686921296317.3004166666667-0.003547453703704150.0431307870370397
6717.3917.347424768518517.35875-0.0113252314814820.0425752314814822
6817.4317.391174768518517.41125-0.02007523148148050.0388252314814821
6917.4517.448466435185217.4591666666667-0.01070023148148080.00153356481481381
7017.517.488049768518517.5054166666667-0.01736689814814880.0119502314814852
7117.5617.525966435185217.5479166666667-0.02195023148148120.0340335648148127
7217.6517.551521990740717.5845833333333-0.0330613425925920.0984780092592601
7317.6217.60874421296317.6179166666667-0.009172453703703480.0112557870370438
7417.717.684438657407417.64958333333330.03485532407407390.0155613425925942
7517.7217.726452546296317.68208333333330.0443692129629627-0.00645254629629477
7617.7117.743674768518517.7150.0286747685185181-0.0336747685185195
7717.7417.763883101851817.74458333333330.019299768518518-0.0238831018518511
7817.7517.76686921296317.7704166666667-0.00354745370370415-0.0168692129629626
7917.78NANA-0.011325231481482NA
8017.8NANA-0.0200752314814805NA
8117.86NANA-0.0107002314814808NA
8217.88NANA-0.0173668981481488NA
8317.89NANA-0.0219502314814812NA
8417.94NANA-0.033061342592592NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 14.14 & NA & NA & -0.00917245370370348 & NA \tabularnewline
2 & 14.16 & NA & NA & 0.0348553240740739 & NA \tabularnewline
3 & 14.21 & NA & NA & 0.0443692129629627 & NA \tabularnewline
4 & 14.26 & NA & NA & 0.0286747685185181 & NA \tabularnewline
5 & 14.29 & NA & NA & 0.019299768518518 & NA \tabularnewline
6 & 14.32 & NA & NA & -0.00354745370370415 & NA \tabularnewline
7 & 14.33 & 14.3349247685185 & 14.34625 & -0.011325231481482 & -0.0049247685185172 \tabularnewline
8 & 14.39 & 14.3599247685185 & 14.38 & -0.0200752314814805 & 0.0300752314814829 \tabularnewline
9 & 14.48 & 14.4038831018519 & 14.4145833333333 & -0.0107002314814808 & 0.0761168981481504 \tabularnewline
10 & 14.44 & 14.4292997685185 & 14.4466666666667 & -0.0173668981481488 & 0.0107002314814828 \tabularnewline
11 & 14.46 & 14.4530497685185 & 14.475 & -0.0219502314814812 & 0.00695023148148266 \tabularnewline
12 & 14.48 & 14.4690219907407 & 14.5020833333333 & -0.033061342592592 & 0.0109780092592615 \tabularnewline
13 & 14.53 & 14.521244212963 & 14.5304166666667 & -0.00917245370370348 & 0.00875578703703717 \tabularnewline
14 & 14.58 & 14.5927719907407 & 14.5579166666667 & 0.0348553240740739 & -0.01277199074074 \tabularnewline
15 & 14.62 & 14.6277025462963 & 14.5833333333333 & 0.0443692129629627 & -0.00770254629629719 \tabularnewline
16 & 14.62 & 14.6411747685185 & 14.6125 & 0.0286747685185181 & -0.0211747685185184 \tabularnewline
17 & 14.61 & 14.6663831018519 & 14.6470833333333 & 0.019299768518518 & -0.0563831018518517 \tabularnewline
18 & 14.65 & 14.6785358796296 & 14.6820833333333 & -0.00354745370370415 & -0.0285358796296276 \tabularnewline
19 & 14.68 & 14.7128414351852 & 14.7241666666667 & -0.011325231481482 & -0.0328414351851833 \tabularnewline
20 & 14.7 & 14.7570081018519 & 14.7770833333333 & -0.0200752314814805 & -0.0570081018518511 \tabularnewline
21 & 14.78 & 14.8238831018519 & 14.8345833333333 & -0.0107002314814808 & -0.0438831018518524 \tabularnewline
22 & 14.84 & 14.8776331018519 & 14.895 & -0.0173668981481488 & -0.037633101851851 \tabularnewline
23 & 14.89 & 14.9367997685185 & 14.95875 & -0.0219502314814812 & -0.0467997685185182 \tabularnewline
24 & 14.89 & 14.9898553240741 & 15.0229166666667 & -0.033061342592592 & -0.0998553240740723 \tabularnewline
25 & 15.13 & 15.0754108796296 & 15.0845833333333 & -0.00917245370370348 & 0.0545891203703732 \tabularnewline
26 & 15.25 & 15.1819386574074 & 15.1470833333333 & 0.0348553240740739 & 0.0680613425925909 \tabularnewline
27 & 15.33 & 15.2552025462963 & 15.2108333333333 & 0.0443692129629627 & 0.0747974537037042 \tabularnewline
28 & 15.36 & 15.3007581018519 & 15.2720833333333 & 0.0286747685185181 & 0.059241898148148 \tabularnewline
29 & 15.4 & 15.3501331018519 & 15.3308333333333 & 0.019299768518518 & 0.0498668981481476 \tabularnewline
30 & 15.4 & 15.388119212963 & 15.3916666666667 & -0.00354745370370415 & 0.0118807870370379 \tabularnewline
31 & 15.41 & 15.4378414351852 & 15.4491666666667 & -0.011325231481482 & -0.0278414351851843 \tabularnewline
32 & 15.47 & 15.4803414351852 & 15.5004166666667 & -0.0200752314814805 & -0.0103414351851825 \tabularnewline
33 & 15.54 & 15.5384664351852 & 15.5491666666667 & -0.0107002314814808 & 0.00153356481481737 \tabularnewline
34 & 15.55 & 15.5792997685185 & 15.5966666666667 & -0.0173668981481488 & -0.0292997685185146 \tabularnewline
35 & 15.59 & 15.6209664351852 & 15.6429166666667 & -0.0219502314814812 & -0.0309664351851833 \tabularnewline
36 & 15.65 & 15.6548553240741 & 15.6879166666667 & -0.033061342592592 & -0.00485532407407163 \tabularnewline
37 & 15.75 & 15.7258275462963 & 15.735 & -0.00917245370370348 & 0.024172453703704 \tabularnewline
38 & 15.86 & 15.8156886574074 & 15.7808333333333 & 0.0348553240740739 & 0.044311342592593 \tabularnewline
39 & 15.89 & 15.8685358796296 & 15.8241666666667 & 0.0443692129629627 & 0.0214641203703732 \tabularnewline
40 & 15.94 & 15.8965914351852 & 15.8679166666667 & 0.0286747685185181 & 0.043408564814813 \tabularnewline
41 & 15.93 & 15.9292997685185 & 15.91 & 0.019299768518518 & 0.000700231481481239 \tabularnewline
42 & 15.95 & 15.945619212963 & 15.9491666666667 & -0.00354745370370415 & 0.00438078703703759 \tabularnewline
43 & 15.99 & 15.9736747685185 & 15.985 & -0.011325231481482 & 0.016325231481483 \tabularnewline
44 & 15.99 & 15.9949247685185 & 16.015 & -0.0200752314814805 & -0.0049247685185172 \tabularnewline
45 & 16.06 & 16.0347164351852 & 16.0454166666667 & -0.0107002314814808 & 0.0252835648148135 \tabularnewline
46 & 16.08 & 16.0651331018518 & 16.0825 & -0.0173668981481488 & 0.0148668981481492 \tabularnewline
47 & 16.07 & 16.1038831018518 & 16.1258333333333 & -0.0219502314814812 & -0.0338831018518491 \tabularnewline
48 & 16.11 & 16.1390219907407 & 16.1720833333333 & -0.033061342592592 & -0.0290219907407412 \tabularnewline
49 & 16.15 & 16.2104108796296 & 16.2195833333333 & -0.00917245370370348 & -0.0604108796296288 \tabularnewline
50 & 16.18 & 16.3061053240741 & 16.27125 & 0.0348553240740739 & -0.126105324074071 \tabularnewline
51 & 16.3 & 16.3677025462963 & 16.3233333333333 & 0.0443692129629627 & -0.0677025462962924 \tabularnewline
52 & 16.42 & 16.4074247685185 & 16.37875 & 0.0286747685185181 & 0.0125752314814882 \tabularnewline
53 & 16.49 & 16.4634664351852 & 16.4441666666667 & 0.019299768518518 & 0.0265335648148159 \tabularnewline
54 & 16.5 & 16.509369212963 & 16.5129166666667 & -0.00354745370370415 & -0.00936921296296234 \tabularnewline
55 & 16.58 & 16.5686747685185 & 16.58 & -0.011325231481482 & 0.0113252314814822 \tabularnewline
56 & 16.64 & 16.6320081018518 & 16.6520833333333 & -0.0200752314814805 & 0.00799189814815193 \tabularnewline
57 & 16.66 & 16.7159664351852 & 16.7266666666667 & -0.0107002314814808 & -0.0559664351851836 \tabularnewline
58 & 16.81 & 16.7759664351852 & 16.7933333333333 & -0.0173668981481488 & 0.0340335648148162 \tabularnewline
59 & 16.91 & 16.8347164351852 & 16.8566666666667 & -0.0219502314814812 & 0.0752835648148142 \tabularnewline
60 & 16.92 & 16.8911053240741 & 16.9241666666667 & -0.033061342592592 & 0.0288946759259296 \tabularnewline
61 & 16.95 & 16.983744212963 & 16.9929166666667 & -0.00917245370370348 & -0.0337442129629615 \tabularnewline
62 & 17.11 & 17.0944386574074 & 17.0595833333333 & 0.0348553240740739 & 0.0155613425925978 \tabularnewline
63 & 17.16 & 17.1697858796296 & 17.1254166666667 & 0.0443692129629627 & -0.00978587962962862 \tabularnewline
64 & 17.16 & 17.2157581018518 & 17.1870833333333 & 0.0286747685185181 & -0.0557581018518469 \tabularnewline
65 & 17.27 & 17.2622164351852 & 17.2429166666667 & 0.019299768518518 & 0.00778356481481879 \tabularnewline
66 & 17.34 & 17.296869212963 & 17.3004166666667 & -0.00354745370370415 & 0.0431307870370397 \tabularnewline
67 & 17.39 & 17.3474247685185 & 17.35875 & -0.011325231481482 & 0.0425752314814822 \tabularnewline
68 & 17.43 & 17.3911747685185 & 17.41125 & -0.0200752314814805 & 0.0388252314814821 \tabularnewline
69 & 17.45 & 17.4484664351852 & 17.4591666666667 & -0.0107002314814808 & 0.00153356481481381 \tabularnewline
70 & 17.5 & 17.4880497685185 & 17.5054166666667 & -0.0173668981481488 & 0.0119502314814852 \tabularnewline
71 & 17.56 & 17.5259664351852 & 17.5479166666667 & -0.0219502314814812 & 0.0340335648148127 \tabularnewline
72 & 17.65 & 17.5515219907407 & 17.5845833333333 & -0.033061342592592 & 0.0984780092592601 \tabularnewline
73 & 17.62 & 17.608744212963 & 17.6179166666667 & -0.00917245370370348 & 0.0112557870370438 \tabularnewline
74 & 17.7 & 17.6844386574074 & 17.6495833333333 & 0.0348553240740739 & 0.0155613425925942 \tabularnewline
75 & 17.72 & 17.7264525462963 & 17.6820833333333 & 0.0443692129629627 & -0.00645254629629477 \tabularnewline
76 & 17.71 & 17.7436747685185 & 17.715 & 0.0286747685185181 & -0.0336747685185195 \tabularnewline
77 & 17.74 & 17.7638831018518 & 17.7445833333333 & 0.019299768518518 & -0.0238831018518511 \tabularnewline
78 & 17.75 & 17.766869212963 & 17.7704166666667 & -0.00354745370370415 & -0.0168692129629626 \tabularnewline
79 & 17.78 & NA & NA & -0.011325231481482 & NA \tabularnewline
80 & 17.8 & NA & NA & -0.0200752314814805 & NA \tabularnewline
81 & 17.86 & NA & NA & -0.0107002314814808 & NA \tabularnewline
82 & 17.88 & NA & NA & -0.0173668981481488 & NA \tabularnewline
83 & 17.89 & NA & NA & -0.0219502314814812 & NA \tabularnewline
84 & 17.94 & NA & NA & -0.033061342592592 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161199&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]14.14[/C][C]NA[/C][C]NA[/C][C]-0.00917245370370348[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]14.16[/C][C]NA[/C][C]NA[/C][C]0.0348553240740739[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]14.21[/C][C]NA[/C][C]NA[/C][C]0.0443692129629627[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]14.26[/C][C]NA[/C][C]NA[/C][C]0.0286747685185181[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]14.29[/C][C]NA[/C][C]NA[/C][C]0.019299768518518[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]14.32[/C][C]NA[/C][C]NA[/C][C]-0.00354745370370415[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]14.33[/C][C]14.3349247685185[/C][C]14.34625[/C][C]-0.011325231481482[/C][C]-0.0049247685185172[/C][/ROW]
[ROW][C]8[/C][C]14.39[/C][C]14.3599247685185[/C][C]14.38[/C][C]-0.0200752314814805[/C][C]0.0300752314814829[/C][/ROW]
[ROW][C]9[/C][C]14.48[/C][C]14.4038831018519[/C][C]14.4145833333333[/C][C]-0.0107002314814808[/C][C]0.0761168981481504[/C][/ROW]
[ROW][C]10[/C][C]14.44[/C][C]14.4292997685185[/C][C]14.4466666666667[/C][C]-0.0173668981481488[/C][C]0.0107002314814828[/C][/ROW]
[ROW][C]11[/C][C]14.46[/C][C]14.4530497685185[/C][C]14.475[/C][C]-0.0219502314814812[/C][C]0.00695023148148266[/C][/ROW]
[ROW][C]12[/C][C]14.48[/C][C]14.4690219907407[/C][C]14.5020833333333[/C][C]-0.033061342592592[/C][C]0.0109780092592615[/C][/ROW]
[ROW][C]13[/C][C]14.53[/C][C]14.521244212963[/C][C]14.5304166666667[/C][C]-0.00917245370370348[/C][C]0.00875578703703717[/C][/ROW]
[ROW][C]14[/C][C]14.58[/C][C]14.5927719907407[/C][C]14.5579166666667[/C][C]0.0348553240740739[/C][C]-0.01277199074074[/C][/ROW]
[ROW][C]15[/C][C]14.62[/C][C]14.6277025462963[/C][C]14.5833333333333[/C][C]0.0443692129629627[/C][C]-0.00770254629629719[/C][/ROW]
[ROW][C]16[/C][C]14.62[/C][C]14.6411747685185[/C][C]14.6125[/C][C]0.0286747685185181[/C][C]-0.0211747685185184[/C][/ROW]
[ROW][C]17[/C][C]14.61[/C][C]14.6663831018519[/C][C]14.6470833333333[/C][C]0.019299768518518[/C][C]-0.0563831018518517[/C][/ROW]
[ROW][C]18[/C][C]14.65[/C][C]14.6785358796296[/C][C]14.6820833333333[/C][C]-0.00354745370370415[/C][C]-0.0285358796296276[/C][/ROW]
[ROW][C]19[/C][C]14.68[/C][C]14.7128414351852[/C][C]14.7241666666667[/C][C]-0.011325231481482[/C][C]-0.0328414351851833[/C][/ROW]
[ROW][C]20[/C][C]14.7[/C][C]14.7570081018519[/C][C]14.7770833333333[/C][C]-0.0200752314814805[/C][C]-0.0570081018518511[/C][/ROW]
[ROW][C]21[/C][C]14.78[/C][C]14.8238831018519[/C][C]14.8345833333333[/C][C]-0.0107002314814808[/C][C]-0.0438831018518524[/C][/ROW]
[ROW][C]22[/C][C]14.84[/C][C]14.8776331018519[/C][C]14.895[/C][C]-0.0173668981481488[/C][C]-0.037633101851851[/C][/ROW]
[ROW][C]23[/C][C]14.89[/C][C]14.9367997685185[/C][C]14.95875[/C][C]-0.0219502314814812[/C][C]-0.0467997685185182[/C][/ROW]
[ROW][C]24[/C][C]14.89[/C][C]14.9898553240741[/C][C]15.0229166666667[/C][C]-0.033061342592592[/C][C]-0.0998553240740723[/C][/ROW]
[ROW][C]25[/C][C]15.13[/C][C]15.0754108796296[/C][C]15.0845833333333[/C][C]-0.00917245370370348[/C][C]0.0545891203703732[/C][/ROW]
[ROW][C]26[/C][C]15.25[/C][C]15.1819386574074[/C][C]15.1470833333333[/C][C]0.0348553240740739[/C][C]0.0680613425925909[/C][/ROW]
[ROW][C]27[/C][C]15.33[/C][C]15.2552025462963[/C][C]15.2108333333333[/C][C]0.0443692129629627[/C][C]0.0747974537037042[/C][/ROW]
[ROW][C]28[/C][C]15.36[/C][C]15.3007581018519[/C][C]15.2720833333333[/C][C]0.0286747685185181[/C][C]0.059241898148148[/C][/ROW]
[ROW][C]29[/C][C]15.4[/C][C]15.3501331018519[/C][C]15.3308333333333[/C][C]0.019299768518518[/C][C]0.0498668981481476[/C][/ROW]
[ROW][C]30[/C][C]15.4[/C][C]15.388119212963[/C][C]15.3916666666667[/C][C]-0.00354745370370415[/C][C]0.0118807870370379[/C][/ROW]
[ROW][C]31[/C][C]15.41[/C][C]15.4378414351852[/C][C]15.4491666666667[/C][C]-0.011325231481482[/C][C]-0.0278414351851843[/C][/ROW]
[ROW][C]32[/C][C]15.47[/C][C]15.4803414351852[/C][C]15.5004166666667[/C][C]-0.0200752314814805[/C][C]-0.0103414351851825[/C][/ROW]
[ROW][C]33[/C][C]15.54[/C][C]15.5384664351852[/C][C]15.5491666666667[/C][C]-0.0107002314814808[/C][C]0.00153356481481737[/C][/ROW]
[ROW][C]34[/C][C]15.55[/C][C]15.5792997685185[/C][C]15.5966666666667[/C][C]-0.0173668981481488[/C][C]-0.0292997685185146[/C][/ROW]
[ROW][C]35[/C][C]15.59[/C][C]15.6209664351852[/C][C]15.6429166666667[/C][C]-0.0219502314814812[/C][C]-0.0309664351851833[/C][/ROW]
[ROW][C]36[/C][C]15.65[/C][C]15.6548553240741[/C][C]15.6879166666667[/C][C]-0.033061342592592[/C][C]-0.00485532407407163[/C][/ROW]
[ROW][C]37[/C][C]15.75[/C][C]15.7258275462963[/C][C]15.735[/C][C]-0.00917245370370348[/C][C]0.024172453703704[/C][/ROW]
[ROW][C]38[/C][C]15.86[/C][C]15.8156886574074[/C][C]15.7808333333333[/C][C]0.0348553240740739[/C][C]0.044311342592593[/C][/ROW]
[ROW][C]39[/C][C]15.89[/C][C]15.8685358796296[/C][C]15.8241666666667[/C][C]0.0443692129629627[/C][C]0.0214641203703732[/C][/ROW]
[ROW][C]40[/C][C]15.94[/C][C]15.8965914351852[/C][C]15.8679166666667[/C][C]0.0286747685185181[/C][C]0.043408564814813[/C][/ROW]
[ROW][C]41[/C][C]15.93[/C][C]15.9292997685185[/C][C]15.91[/C][C]0.019299768518518[/C][C]0.000700231481481239[/C][/ROW]
[ROW][C]42[/C][C]15.95[/C][C]15.945619212963[/C][C]15.9491666666667[/C][C]-0.00354745370370415[/C][C]0.00438078703703759[/C][/ROW]
[ROW][C]43[/C][C]15.99[/C][C]15.9736747685185[/C][C]15.985[/C][C]-0.011325231481482[/C][C]0.016325231481483[/C][/ROW]
[ROW][C]44[/C][C]15.99[/C][C]15.9949247685185[/C][C]16.015[/C][C]-0.0200752314814805[/C][C]-0.0049247685185172[/C][/ROW]
[ROW][C]45[/C][C]16.06[/C][C]16.0347164351852[/C][C]16.0454166666667[/C][C]-0.0107002314814808[/C][C]0.0252835648148135[/C][/ROW]
[ROW][C]46[/C][C]16.08[/C][C]16.0651331018518[/C][C]16.0825[/C][C]-0.0173668981481488[/C][C]0.0148668981481492[/C][/ROW]
[ROW][C]47[/C][C]16.07[/C][C]16.1038831018518[/C][C]16.1258333333333[/C][C]-0.0219502314814812[/C][C]-0.0338831018518491[/C][/ROW]
[ROW][C]48[/C][C]16.11[/C][C]16.1390219907407[/C][C]16.1720833333333[/C][C]-0.033061342592592[/C][C]-0.0290219907407412[/C][/ROW]
[ROW][C]49[/C][C]16.15[/C][C]16.2104108796296[/C][C]16.2195833333333[/C][C]-0.00917245370370348[/C][C]-0.0604108796296288[/C][/ROW]
[ROW][C]50[/C][C]16.18[/C][C]16.3061053240741[/C][C]16.27125[/C][C]0.0348553240740739[/C][C]-0.126105324074071[/C][/ROW]
[ROW][C]51[/C][C]16.3[/C][C]16.3677025462963[/C][C]16.3233333333333[/C][C]0.0443692129629627[/C][C]-0.0677025462962924[/C][/ROW]
[ROW][C]52[/C][C]16.42[/C][C]16.4074247685185[/C][C]16.37875[/C][C]0.0286747685185181[/C][C]0.0125752314814882[/C][/ROW]
[ROW][C]53[/C][C]16.49[/C][C]16.4634664351852[/C][C]16.4441666666667[/C][C]0.019299768518518[/C][C]0.0265335648148159[/C][/ROW]
[ROW][C]54[/C][C]16.5[/C][C]16.509369212963[/C][C]16.5129166666667[/C][C]-0.00354745370370415[/C][C]-0.00936921296296234[/C][/ROW]
[ROW][C]55[/C][C]16.58[/C][C]16.5686747685185[/C][C]16.58[/C][C]-0.011325231481482[/C][C]0.0113252314814822[/C][/ROW]
[ROW][C]56[/C][C]16.64[/C][C]16.6320081018518[/C][C]16.6520833333333[/C][C]-0.0200752314814805[/C][C]0.00799189814815193[/C][/ROW]
[ROW][C]57[/C][C]16.66[/C][C]16.7159664351852[/C][C]16.7266666666667[/C][C]-0.0107002314814808[/C][C]-0.0559664351851836[/C][/ROW]
[ROW][C]58[/C][C]16.81[/C][C]16.7759664351852[/C][C]16.7933333333333[/C][C]-0.0173668981481488[/C][C]0.0340335648148162[/C][/ROW]
[ROW][C]59[/C][C]16.91[/C][C]16.8347164351852[/C][C]16.8566666666667[/C][C]-0.0219502314814812[/C][C]0.0752835648148142[/C][/ROW]
[ROW][C]60[/C][C]16.92[/C][C]16.8911053240741[/C][C]16.9241666666667[/C][C]-0.033061342592592[/C][C]0.0288946759259296[/C][/ROW]
[ROW][C]61[/C][C]16.95[/C][C]16.983744212963[/C][C]16.9929166666667[/C][C]-0.00917245370370348[/C][C]-0.0337442129629615[/C][/ROW]
[ROW][C]62[/C][C]17.11[/C][C]17.0944386574074[/C][C]17.0595833333333[/C][C]0.0348553240740739[/C][C]0.0155613425925978[/C][/ROW]
[ROW][C]63[/C][C]17.16[/C][C]17.1697858796296[/C][C]17.1254166666667[/C][C]0.0443692129629627[/C][C]-0.00978587962962862[/C][/ROW]
[ROW][C]64[/C][C]17.16[/C][C]17.2157581018518[/C][C]17.1870833333333[/C][C]0.0286747685185181[/C][C]-0.0557581018518469[/C][/ROW]
[ROW][C]65[/C][C]17.27[/C][C]17.2622164351852[/C][C]17.2429166666667[/C][C]0.019299768518518[/C][C]0.00778356481481879[/C][/ROW]
[ROW][C]66[/C][C]17.34[/C][C]17.296869212963[/C][C]17.3004166666667[/C][C]-0.00354745370370415[/C][C]0.0431307870370397[/C][/ROW]
[ROW][C]67[/C][C]17.39[/C][C]17.3474247685185[/C][C]17.35875[/C][C]-0.011325231481482[/C][C]0.0425752314814822[/C][/ROW]
[ROW][C]68[/C][C]17.43[/C][C]17.3911747685185[/C][C]17.41125[/C][C]-0.0200752314814805[/C][C]0.0388252314814821[/C][/ROW]
[ROW][C]69[/C][C]17.45[/C][C]17.4484664351852[/C][C]17.4591666666667[/C][C]-0.0107002314814808[/C][C]0.00153356481481381[/C][/ROW]
[ROW][C]70[/C][C]17.5[/C][C]17.4880497685185[/C][C]17.5054166666667[/C][C]-0.0173668981481488[/C][C]0.0119502314814852[/C][/ROW]
[ROW][C]71[/C][C]17.56[/C][C]17.5259664351852[/C][C]17.5479166666667[/C][C]-0.0219502314814812[/C][C]0.0340335648148127[/C][/ROW]
[ROW][C]72[/C][C]17.65[/C][C]17.5515219907407[/C][C]17.5845833333333[/C][C]-0.033061342592592[/C][C]0.0984780092592601[/C][/ROW]
[ROW][C]73[/C][C]17.62[/C][C]17.608744212963[/C][C]17.6179166666667[/C][C]-0.00917245370370348[/C][C]0.0112557870370438[/C][/ROW]
[ROW][C]74[/C][C]17.7[/C][C]17.6844386574074[/C][C]17.6495833333333[/C][C]0.0348553240740739[/C][C]0.0155613425925942[/C][/ROW]
[ROW][C]75[/C][C]17.72[/C][C]17.7264525462963[/C][C]17.6820833333333[/C][C]0.0443692129629627[/C][C]-0.00645254629629477[/C][/ROW]
[ROW][C]76[/C][C]17.71[/C][C]17.7436747685185[/C][C]17.715[/C][C]0.0286747685185181[/C][C]-0.0336747685185195[/C][/ROW]
[ROW][C]77[/C][C]17.74[/C][C]17.7638831018518[/C][C]17.7445833333333[/C][C]0.019299768518518[/C][C]-0.0238831018518511[/C][/ROW]
[ROW][C]78[/C][C]17.75[/C][C]17.766869212963[/C][C]17.7704166666667[/C][C]-0.00354745370370415[/C][C]-0.0168692129629626[/C][/ROW]
[ROW][C]79[/C][C]17.78[/C][C]NA[/C][C]NA[/C][C]-0.011325231481482[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]17.8[/C][C]NA[/C][C]NA[/C][C]-0.0200752314814805[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]17.86[/C][C]NA[/C][C]NA[/C][C]-0.0107002314814808[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]17.88[/C][C]NA[/C][C]NA[/C][C]-0.0173668981481488[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]17.89[/C][C]NA[/C][C]NA[/C][C]-0.0219502314814812[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]17.94[/C][C]NA[/C][C]NA[/C][C]-0.033061342592592[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161199&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161199&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
114.14NANA-0.00917245370370348NA
214.16NANA0.0348553240740739NA
314.21NANA0.0443692129629627NA
414.26NANA0.0286747685185181NA
514.29NANA0.019299768518518NA
614.32NANA-0.00354745370370415NA
714.3314.334924768518514.34625-0.011325231481482-0.0049247685185172
814.3914.359924768518514.38-0.02007523148148050.0300752314814829
914.4814.403883101851914.4145833333333-0.01070023148148080.0761168981481504
1014.4414.429299768518514.4466666666667-0.01736689814814880.0107002314814828
1114.4614.453049768518514.475-0.02195023148148120.00695023148148266
1214.4814.469021990740714.5020833333333-0.0330613425925920.0109780092592615
1314.5314.52124421296314.5304166666667-0.009172453703703480.00875578703703717
1414.5814.592771990740714.55791666666670.0348553240740739-0.01277199074074
1514.6214.627702546296314.58333333333330.0443692129629627-0.00770254629629719
1614.6214.641174768518514.61250.0286747685185181-0.0211747685185184
1714.6114.666383101851914.64708333333330.019299768518518-0.0563831018518517
1814.6514.678535879629614.6820833333333-0.00354745370370415-0.0285358796296276
1914.6814.712841435185214.7241666666667-0.011325231481482-0.0328414351851833
2014.714.757008101851914.7770833333333-0.0200752314814805-0.0570081018518511
2114.7814.823883101851914.8345833333333-0.0107002314814808-0.0438831018518524
2214.8414.877633101851914.895-0.0173668981481488-0.037633101851851
2314.8914.936799768518514.95875-0.0219502314814812-0.0467997685185182
2414.8914.989855324074115.0229166666667-0.033061342592592-0.0998553240740723
2515.1315.075410879629615.0845833333333-0.009172453703703480.0545891203703732
2615.2515.181938657407415.14708333333330.03485532407407390.0680613425925909
2715.3315.255202546296315.21083333333330.04436921296296270.0747974537037042
2815.3615.300758101851915.27208333333330.02867476851851810.059241898148148
2915.415.350133101851915.33083333333330.0192997685185180.0498668981481476
3015.415.38811921296315.3916666666667-0.003547453703704150.0118807870370379
3115.4115.437841435185215.4491666666667-0.011325231481482-0.0278414351851843
3215.4715.480341435185215.5004166666667-0.0200752314814805-0.0103414351851825
3315.5415.538466435185215.5491666666667-0.01070023148148080.00153356481481737
3415.5515.579299768518515.5966666666667-0.0173668981481488-0.0292997685185146
3515.5915.620966435185215.6429166666667-0.0219502314814812-0.0309664351851833
3615.6515.654855324074115.6879166666667-0.033061342592592-0.00485532407407163
3715.7515.725827546296315.735-0.009172453703703480.024172453703704
3815.8615.815688657407415.78083333333330.03485532407407390.044311342592593
3915.8915.868535879629615.82416666666670.04436921296296270.0214641203703732
4015.9415.896591435185215.86791666666670.02867476851851810.043408564814813
4115.9315.929299768518515.910.0192997685185180.000700231481481239
4215.9515.94561921296315.9491666666667-0.003547453703704150.00438078703703759
4315.9915.973674768518515.985-0.0113252314814820.016325231481483
4415.9915.994924768518516.015-0.0200752314814805-0.0049247685185172
4516.0616.034716435185216.0454166666667-0.01070023148148080.0252835648148135
4616.0816.065133101851816.0825-0.01736689814814880.0148668981481492
4716.0716.103883101851816.1258333333333-0.0219502314814812-0.0338831018518491
4816.1116.139021990740716.1720833333333-0.033061342592592-0.0290219907407412
4916.1516.210410879629616.2195833333333-0.00917245370370348-0.0604108796296288
5016.1816.306105324074116.271250.0348553240740739-0.126105324074071
5116.316.367702546296316.32333333333330.0443692129629627-0.0677025462962924
5216.4216.407424768518516.378750.02867476851851810.0125752314814882
5316.4916.463466435185216.44416666666670.0192997685185180.0265335648148159
5416.516.50936921296316.5129166666667-0.00354745370370415-0.00936921296296234
5516.5816.568674768518516.58-0.0113252314814820.0113252314814822
5616.6416.632008101851816.6520833333333-0.02007523148148050.00799189814815193
5716.6616.715966435185216.7266666666667-0.0107002314814808-0.0559664351851836
5816.8116.775966435185216.7933333333333-0.01736689814814880.0340335648148162
5916.9116.834716435185216.8566666666667-0.02195023148148120.0752835648148142
6016.9216.891105324074116.9241666666667-0.0330613425925920.0288946759259296
6116.9516.98374421296316.9929166666667-0.00917245370370348-0.0337442129629615
6217.1117.094438657407417.05958333333330.03485532407407390.0155613425925978
6317.1617.169785879629617.12541666666670.0443692129629627-0.00978587962962862
6417.1617.215758101851817.18708333333330.0286747685185181-0.0557581018518469
6517.2717.262216435185217.24291666666670.0192997685185180.00778356481481879
6617.3417.29686921296317.3004166666667-0.003547453703704150.0431307870370397
6717.3917.347424768518517.35875-0.0113252314814820.0425752314814822
6817.4317.391174768518517.41125-0.02007523148148050.0388252314814821
6917.4517.448466435185217.4591666666667-0.01070023148148080.00153356481481381
7017.517.488049768518517.5054166666667-0.01736689814814880.0119502314814852
7117.5617.525966435185217.5479166666667-0.02195023148148120.0340335648148127
7217.6517.551521990740717.5845833333333-0.0330613425925920.0984780092592601
7317.6217.60874421296317.6179166666667-0.009172453703703480.0112557870370438
7417.717.684438657407417.64958333333330.03485532407407390.0155613425925942
7517.7217.726452546296317.68208333333330.0443692129629627-0.00645254629629477
7617.7117.743674768518517.7150.0286747685185181-0.0336747685185195
7717.7417.763883101851817.74458333333330.019299768518518-0.0238831018518511
7817.7517.76686921296317.7704166666667-0.00354745370370415-0.0168692129629626
7917.78NANA-0.011325231481482NA
8017.8NANA-0.0200752314814805NA
8117.86NANA-0.0107002314814808NA
8217.88NANA-0.0173668981481488NA
8317.89NANA-0.0219502314814812NA
8417.94NANA-0.033061342592592NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')